{
 "metadata": {
  "name": ""
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%pylab inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Populating the interactive namespace from numpy and matplotlib\n"
       ]
      }
     ],
     "prompt_number": 16
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from __future__ import division"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 17
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import instruments as ik"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "scope=ik.tektronix.TekDPO70000Series.open_tcpip('192.168.0.4',4005)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "scope._file._debug = True"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "scope._file.timeout = 2"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "scope.query('*IDN?')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " <- '*IDN?\\n' \n",
        " -> 'TEKTRONIX,DPO71254C,B130126,CF:91.1CT FV:5.3.0 Build 83\\n'\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "'TEKTRONIX,DPO71254C,B130126,CF:91.1CT FV:5.3.0 Build 83\\n'"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ch0 = scope.channel[0]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ch0.bandwidth"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " <- 'CH1:BAN?\\n' \n",
        " -> '12.5000E+9\\n'\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "array(12500000000.0) * Hz"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "_.rescale('GHz')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 8,
       "text": [
        "array(12.5) * GHz"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "scope.outgoing_waveform_encoding = scope.WaveformEncoding.binary"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " <- 'WFMO:ENC BINARY\\n' \n"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "scope.select_fastest_encoding()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " <- 'DAT:ENC FAS\\n' \n"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "scope.acquire_mode_actual"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "timeout",
       "evalue": "timed out",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mtimeout\u001b[0m                                   Traceback (most recent call last)",
        "\u001b[1;32m<ipython-input-11-fc328e0e3863>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mscope\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0macquire_mode_actual\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
        "\u001b[1;32mC:\\Users\\fpga\\AppData\\Local\\Enthought\\Canopy\\User\\lib\\site-packages\\instruments\\util_fns.pyc\u001b[0m in \u001b[0;36mgetter\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    109\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mval\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0moutput_decoration\u001b[0m \u001b[1;32mis\u001b[0m \u001b[0mNone\u001b[0m \u001b[1;32melse\u001b[0m \u001b[0moutput_decoration\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mval\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    110\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mgetter\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 111\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0menum\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0min_decor_fcn\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mquery\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"{}?\"\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstrip\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    112\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0msetter\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnewval\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    113\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msendcmd\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"{} {}\"\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mout_decor_fcn\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0menum\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mnewval\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvalue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32mC:\\Users\\fpga\\AppData\\Local\\Enthought\\Canopy\\User\\lib\\site-packages\\instruments\\abstract_instruments\\instrument.pyc\u001b[0m in \u001b[0;36mquery\u001b[1;34m(self, cmd, size)\u001b[0m\n\u001b[0;32m    111\u001b[0m         \u001b[1;33m:\u001b[0m\u001b[0mrtype\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;33m`\u001b[0m\u001b[0mstr\u001b[0m\u001b[1;33m`\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    112\u001b[0m         \"\"\"\n\u001b[1;32m--> 113\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_file\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mquery\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcmd\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msize\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    114\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    115\u001b[0m     \u001b[1;31m## PROPERTIES ##\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32mC:\\Users\\fpga\\AppData\\Local\\Enthought\\Canopy\\User\\lib\\site-packages\\instruments\\abstract_instruments\\socketwrapper.pyc\u001b[0m in \u001b[0;36mquery\u001b[1;34m(self, msg, size)\u001b[0m\n\u001b[0;32m    139\u001b[0m         '''\n\u001b[0;32m    140\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msendcmd\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 141\u001b[1;33m         \u001b[0mresp\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msize\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    142\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_debug\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    143\u001b[0m             \u001b[1;32mprint\u001b[0m \u001b[1;34m\" -> {}\"\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrepr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mresp\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32mC:\\Users\\fpga\\AppData\\Local\\Enthought\\Canopy\\User\\lib\\site-packages\\instruments\\abstract_instruments\\socketwrapper.pyc\u001b[0m in \u001b[0;36mread\u001b[1;34m(self, size)\u001b[0m\n\u001b[0;32m    103\u001b[0m             \u001b[0mc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    104\u001b[0m             \u001b[1;32mwhile\u001b[0m \u001b[0mc\u001b[0m \u001b[1;33m!=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_terminator\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 105\u001b[1;33m                 \u001b[0mc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_conn\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrecv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    106\u001b[0m                 \u001b[0mresult\u001b[0m \u001b[1;33m+=\u001b[0m \u001b[0mc\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    107\u001b[0m             \u001b[1;32mreturn\u001b[0m \u001b[0mbytes\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;31mtimeout\u001b[0m: timed out"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " <- 'ACQ:MOD:ACT?\\n' \n"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "wav0 = ch0.read_waveform()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " <- 'DAT:SOU?\\n' \n",
        " -> 'CH1\\n'\n",
        " <- 'DAT:SOU CH1\\n' \n",
        " <- 'DAT:ENC FAS\\n' \n",
        " <- 'WFMO:BYT_N?\\n' \n",
        " -> '2\\n'"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        " <- 'WFMO:BN_F?\\n' \n",
        " -> 'RI\\n'\n",
        " <- 'WFMO:BYT_O?\\n' \n",
        " -> 'LSB\\n'\n",
        " <- 'CURV?\\n' \n",
        " <- 'CH1:SCALE?\\n' \n",
        " -> '100.0000E-3\\n'\n",
        " <- 'CH1:POS?\\n' \n",
        " -> '0.0000\\n'\n",
        " <- 'CH1:OFFS?\\n' \n",
        " -> '0.0000\\n'\n",
        " <- 'DAT:SOU CH1\\n' \n"
       ]
      }
     ],
     "prompt_number": 13
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plot(wav0.magnitude)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 15,
       "text": [
        "[<matplotlib.lines.Line2D at 0x866bd30>]"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEACAYAAACd2SCPAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nEQgyIARBEEQg/j8lnQrZEk2SlgAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x82bbac8>"
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}